Sharif Digital Repository

A distinct viewpoint is adopted by each centrality to analyze a network and rank its nodes. This study aims to introduce a novel centrality that ranks the nodes of a network more effectively. In this respect, a function of five centralities, namely betweenness, closeness, agent vector, degree, and Katz, is introduced to maximize the connected components of the network after ranking its nodes and deleting the first twenty ones. The proposed centrality functions better than the other mentioned centralities. Among the networks simulated to evaluate the centrality, it functions better in Erdos-Renyi and small-world networks, both of whom being based on the Poisson degree distribution, and...